Purpose :
Although Stargardt disease was originally characterized as a juvenile form of macular degeneration, it manifests itself in a far wider age range between the first and seventh decade of life. Despite our growing understanding of the underlying mechanisms, predicting the clinical course of Stargardt disease remains a challenge. We hypothesize that an age-specific incidence distribution reflects differences in disease progression. Such a correlation would improve our prediction of the clinical course in individual patients.

Methods :
We selected 229 patients with a clinical diagnosis of Stargardt disease, supported by at least one ABCA4 variant, and with at least one available color fundus photograph, fundus autofluorescence, or near-infrared reflectance image. We classified patients based on two established natural courses, without taking into account the age at onset: A, rapid retina-wide degeneration with initial foveal loss; and B, slowly progressive, foveal sparing retinal degeneration. Patients who did not fit either course were categorized as such (course X). The odds ratios and 95% confidence intervals (CI) for a patient to fall into a natural course by age at onset were calculated using multinomial logistic regression.

Results :
We classified 66 patients into course A, and 49 into course B. The remaining 114 patients were classified into course X. The age at onset was associated with lower odds of rapid retina-wide degeneration (OR: 0.599, 95%CI: 0.513 – 0.700) with 50% probability at a disease onset of 12 years. Age at onset was also associated with higher odds of a natural course with foveal sparing (OR: 1.318, 95%CI: 1.188 – 1.460) with 50% probability at 41 years.

Conclusions :
Our data identified a distinct age-specific incidence distribution of progression types, indicating that at least three subtypes of disease progression can be predicted based on the age at onset: (A) early-onset Stargardt (<12 years), (X) intermediate-onset Stargardt (12 – 41 years), and (B) late-onset Stargardt (>42 years). However, the overlap with regard to age at onset between subtypes allows other variables, such as electroretinography and genotype, to predict the eventual natural course more precisely. Furthermore, the prognostic variability within intermediate-onset Stargardt can be further elucidated.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.